Atmospheric Data Scientist (Senior/Staff)

What we are looking for

We are looking for an experienced Atmospheric Data Scientist with a strong background in meteorology, data engineering, and machine learning (ML). The ideal candidate will have a deep understanding of weather phenomena, predictability patterns of underlying numerical weather prediction models, and developing ML solutions for predicting derivative products. You should be proficient in handling large datasets, developing predictive models, and communicating weather predictability to non-atmospheric scientists.  A strong preference will be given to experience in developing probabilistic models using various machine learning methods.

What you will do

You will be a leading expert in weather modeling across the enterprise with frequent cross-functional communication to learn weather related business challenges and collaborate internally with other science and engineering team members to develop predictive models to solve those business problems. Your work will involve analyzing atmospheric data, creating predictive models, and collaborating with cross-functional teams to ensure our battery storage systems operate at peak efficiency.

Responsibilities

• Influence product and engineering roadmaps by presenting research insights, experimental results, and model performance metrics related to atmospheric data and its impact on energy markets.

• Develop sophisticated models and tools that analyze the behavior of electricity markets, incorporating atmospheric data to predict power prices, ancillary services dispatch, grid network models, transmission outages, and constraints.

• Leverage advanced weather forecasting and atmospheric data models to inform strategic decisions and evolve organizational direction.

• Initiate and lead cross-functional engagements to address complex and ambiguous challenges where innovative atmospheric science research can drive significant company impact, prioritizing initiatives that integrate atmospheric data with energy market optimization.

• Tackle complex scientific and operations research problems by integrating atmospheric data insights with existing energy optimization frameworks.

• Develop and lead medium to long-term ML modeling projects focused on advancing the state-of-the-art in integrating atmospheric data with energy asset management and financial trading performance.

The minimum qualifications you’ll need

• Advanced degree (Master's or Ph.D.) in Atmospheric Science, Meteorology, Data Science, or a related field.

• Proven experience in atmospheric data analysis and forecasting.

• Strong programming skills in Python.

• Expertise in machine learning algorithms and statistical modeling.

• Experience communicating to non-atmospheric scientists deeply technical weather prediction challenges and solutions.

• Knowledge of energy markets and renewable energy systems is a plus.

• Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team environment.

Nice to have additional skills

• Demonstrated experience with developing and releasing operational probabilistic ML prediction models in the weather and/or energy sector

• Experience with forecasting & time series problems

• Experience with multiple Numerical Weather Prediction (NWP) models

• Demonstrated track record of academic paper or social media publication 

• Experience with experiment tracking and presenting results to non-technical audiences

• Experience with various US energy markets, including PJM, ERCOT, SPP, MISO, NYISO, ISO-NE, and CAISO